IBM Integrated Analytics System

Feature spotlights

Built-in tools for data scientists

Use Jupyter Notebooks or the built-in Data Science Experience feature to quickly connect to system data and begin modeling immediately. Data scientists can access data regardless of location or data type. This allows them to maximize the value of their models by using the right data.

Embedded Spark processing with machine learning

Common SQL engine

Shares a common analytics engine with other offerings in the IBM hybrid data management portfolio. The technology decouples the analytics application and data storage, enabling applications to work transparently with on-premise, cloud, RDBMS, NoSQL and Hadoop data sources. With IBM, you can easily move to or from the cloud.

Cloud-ready with scalable deployment

Scale up to petabyte levels. Flexible configurations allow you to expand computing and storage capacity independently, and scale your workload as needed. Features multi-temperature tiered storage. It ensures that highly accessed data resides on high-performance Flash, while older data resides on HDDs, to optimize performance and reduce cost. Workloads required to be in the cloud can also be moved without application rewrites.